Portable near-infrared (NIR) analyzer for classifying the high oleic acid peanuts (HOP) and quantitation of its major fatty acids was assessed for the first time in comparison with the benchtop NIR. Reference chemical values of fatty acids were calculated by the gas chromatographic method. The processed datasets were explored by principal component analysis and classification models were built by using partial least square discriminant analysis. The results showed that the accuracy of distinction of the HOP from others was 100%. Partial least square was used to build quantitative models for quantifying the peanuts’ major fatty acids. The R of the calibration model noted for the portable NIR was 0.90, 0.88 and 0.88 for oleic acid, linoleic acid and palmitic acid of the HOP with a SEC of 0.97, 0.12 and 0.12, respectively. The similar results could be found in the benchtop NIR. The RPD of all models were over 2 which showed good performance of the models. This study indicated that the portable NIR performance was comparable with the performance of the benchtop NIR for distinction of the HOP from others, as well as for the prediction of the contents of its main fatty acids. •The first report on the qualitative and quantitative analysis in peanut kernels by portable NIR.•The interrelationships between HOP and RP were determined by PCA.•HOP and RP were completely distinguished based on PLS-DA by portable and benchtop NIR.•Portable NIR had the same quantitative performance as benchtop NIR according PLS models.